AI Security Architect

Required Skills & Experience
• \tBachelor's degree in technical area and 5+ years of relevant cybersecurity experience, \n•\t2+ years of experience focused on AI Governance or Data Governance. \n•\tWorking knowledge of security frameworks (e.g., NIST, CIS, ISO 27001), compliance regulations, and security best practices.\n•\tStrong problem-solving skills and attention to detail \n•\tStrong communication, collaboration, and interpersonal skills, with the ability to effectively communicate complex technical concepts to diverse audiences, including technical and non-technical stakeholders, partners, and leadership. \n•\tAbility to develop and maintain AI Security Strategy and Roadmap \n•\tAssociates will be responsible for supporting key Security Solutions and Services off hours based on the team on call schedule.

Nice to Have Skills & Experience
• \tProfessional certifications from accredited organization such as ISC2, SANS, ISACA (i.e. CISSP, CISM or SABSA) \n•\t5+ years Cybersecurity Engineering or Architecture Experience\n•\tMaster's degree in Cybersecurity, Information Security, or related field.

Job Description

Our client requires a dedicated AI Security Architect to address the unique and rapidly expanding security risks introduced by artificial intelligence technologies. AI introduces distinct risk domains that are not fully covered by traditional security, cloud, data, or product architecture roles. As AI adoption accelerates and becomes a permanent operational capability, the demands on existing teams continue to grow beyond current capacity and skill sets.\nThis role provides focused ownership and accountability for AI security architecture, governance, and risk mitigation across the enterprise, enabling secure innovation while protecting the organization's data, systems, and reputation.\n\nPosition Responsibilities\nAI Security Strategy & Enablement\n•\tDrive secure adoption of AI technologies and data science best practices (e.g., machine learning models, Claude and other LLMs, model training practices, data quality requirements, data literacy, etc.) within the Security organization.\n•\tPartner with AI, innovation, and engineering teams to enable AI usage aligned with security expectations.\n•\tEstablish guidelines for AI usage within the organization.\n\nGovernance, Risk & Compliance\n•\tSupport and actively participate in the GRC AI Workgroup and AI Taskforce.\n•\tCreate and maintain governance frameworks, policies, and controls to mitigate AI system risks.\n•\tSupport demand reviews by assessing AI initiatives for security, privacy, and risk impact.\n•\tProvide AI security requirements and guidelines to AI innovation teams.\n\nArchitecture & Design\n•\tDesign and maintain secure reference architectures for AI systems, including models, platforms, and integrations.\n•\tEnsure AI systems align with established enterprise security principles across: \no\tCloud\no\tIdentity and access management\no\tNetwork security\no\tDevSecOps\no\tData security\n\nData Protection & AI Risk Mitigation\n•\tSupport ongoing efforts to secure AI model data usage enterprise platforms (i.e.Snowflake and Databricks).\n•\tDrive controls to prevent data loss through public and external LLMs.\n•\tPartner with monitoring and security tooling teams to enhance visibility into AI usage and risk.